Security of Smart Home Intrusion Detection Systems using Data Mining Technique
DOI:
https://doi.org/10.26438/ijcse/v7i6.11691176Keywords:
Smart Home, Intrusion Detection systems, K-Means algorithm, Password, Security, Soft tokenAbstract
Poor security of Smart homes resulting from compromised system password and IP address has been on the increase as a result of hackers’ access to system. For this reason, there is need to introduce tertiary security feature. This work presents comprehensive survey of security challenges in smart home intrusion detection systems using qualitative research methodology. The researcher provided design of tertiary security parameter- Soft token along side IP address and password that serve as primary and secondary parameters to optimize system. Object oriented analysis and design plan was similarly embraced to help indicate the relationship between object and its class. K-means algorithm as data mining clustering technique was used to aid intrusion detection and prevention in smart home i.e. the system was able to differentiate between authorized from unauthorized access and simultaneously, send security warning to the framework administrator’s email whenever there is an intrusion. The development stage was done using some sets of software tools: PHP, HTML, JavaScript, and MySQL database system. Xampp server was used to test-run the system during the development process. Experimental result shows that soft token alongside IP address and password to check for an intrusion was able to optimize security.
References
[1] S. Chitnis, N. Deshpande & A. Shaligram, “An Investigative Study for Smart home security: Issues, challenges and countermeasures”, Wireless Sensor Network, 8(04), 61, 2016.
[2] C. Badica, & M. Brezovan, “A Review on Vision surveillance techniques in smart home environments”, 19th International Conference on Control Systems and Computer Science, pp. 471-478, 2013.
[3] M. Kumar & K. Shinde, “Technical Report on Intruder Detection and Alert System”, arXiv preprint arXiv:1509.09138, 2015.
[4] B. N. Schilit & M. M. Theimer, “Disseminating Active Mop Infonncition to Mobile Hosts”, IEEE network, 1994.
[5] S. M. Tsai, P. C. Yang, S. S. Wu, & S. S. Sun, “A Service of Home security system on Intelligent network”, IEEE Transactions on Consumer Electronics, 44(4), 1360-1366, 1998.
[6] N. Sriskanthan, F. Tan & A. Karande, “Bluetooth Based smart home system. Microprocessors and Microsystems”, 26(6), 281-289, 2002.
[7] A. Alheraish, “Design and Implementation of Smart home system”, IEEE Transactions on Consumer Electronics, 50(4), 1087-1092, 2004.
[8] M. Danaher & D. Nguyen, “Mobile Home Security with GPRS”, ISI, 2002, 377-380, 2002.
[9] L. Yang, S. H. Yang, & F. Yao, “Safety and Security of Remote Monitoring and control of intelligent home environments”, IEEE International Conference on Systems, Man and Cybernetics Vol. 2, pp. 1149-1153, 2006.
[10] L. Muhury & A. A. Habib, “Device control by using GSM network”, 15th International Conference on Computer and Information Technology (ICCIT) IEEE pp. 271-274, 2012.
[11] A. Z. Alkar & U. Buhur, “A Web based Wireless smart home system for multifunctional devices”, IEEE Transactions on Consumer Electronics, 51(4), 1169-1174, 2005.
[12] M. Gauger, D. Minder, P. J. Marron, A. Wacker & A. Lachenmann, “Prototyping Sensor-Actuator Networks for Smart home”, In Proceedings of the workshop on Real-world wireless sensor networks pp. 56-60, 2008.
[13] N.K Denzin & Y.S. Lincoln, “The Sage Handbook of Qualitative Research”, Sage Publications 2017.
[14] E. Colbert, “Requirement Analysis with the Object Oriented Software Development Method”, 1998.
[15] N. Rehman, “Data Mining techniques methods Algorithms and Tools”, International Journal of Computer Sciences and Mobile Computing, Vol. 6 Issue 7, pg 227-231, 2017.
[16] P. Rutravigneshwaran, “A Study of Intrusion Detection System using Efficient Data Mining Techniques”, International Journal of Scientific Research in Network security and Communication, Vol. 5, Issue 6, 2017.
[17] P. Pareta, M. Rai & M. Gangwar, “An Integrated Approach for effective Intrusion Detection with ElasticSearch”, International Journal of Scientific Research in Computer Sciences and Engineering, Vol. 6, Issue 3, pp.13-17, 2018.
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